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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Gulzar, Muhammad Majid Ahmed, Muhammad Mughees Shakoor, Adnan Tahreem, Huma Center for Renewable Energy and Power Systems King Fahd University of Petroleum & Minerals Department of Control & Instrumentation Engineering Dhahran31261 Saudi Arabia University of Central Punjab Department of Electrical Engineering Lahore Pakistan

ISBN: (纸本)9798350304602

In modern automobiles, driving assistance systems are extensively used for efficiency, safety and comfort. These systems are utilized for autonomous driving, cruise control, and obstacle avoidance. All of these systems consist of a large number of radars and sensors that generate rapid responses to control the speed or direction of a vehicle. The primary objective of this type of technology is to reduce accidents by reducing driver tension and enhancing travel comfort. The purpose of this study is to develop a controller for cruise control in vehicles that can precisely, rapidly, and efficiently attain the desired speed. In this study, biological inspired optimization tuned Sliding Mode controller is utilized which is more accurate and robust, and can help to adjust the parameters so that the cruise control system provides minimal error, stable results with the fewest disturbances possible. In order to demonstrate the superiority of the proposed controller, the results are subsequently compared to currently employed cutting-edge technologies for cruise control. © 2023 IEEE.

关键词： Autonomous vehicles

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A Model Predictive control Framework for Improving Risk-Tolerance of Manufacturing systems

A Model Predictive Control Framework for Improving Risk-Tole...

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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Anbarani, Mostafa Tavakkoli Balta, Efe C. Meira-Goes, Romulo Kovalenko, Ilya Pennsylvania State University Department of Mechanical Engineering PA United States Automatic Control Laboratory Eth Zürich Zürich Switzerland Pennsylvania State University Department of Electrical Engineering PA United States Pennsylvania State University Department of Industrial and Manufacturing Engineering PA United States

ISBN: (纸本)9798350335446

The need for control strategies that can address dynamic system uncertainty is becoming increasingly important. In this work, we propose a Model Predictive control for quantifying the risk of failure in our system model. The proposed control scheme uses a Priced Timed Automata representation of the manufacturing system to promote the fail-safe operation of systems under uncertainties. The proposed method ensures that in case of unforeseen failure(s), the optimization-based control strategy can still achieve the manufacturing system objective. In addition, the proposed strategy establishes a trade-off between minimizing the cost and reducing failure risk to allow the manufacturing system to function effectively in the presence of uncertainties. An example from manufacturing systems is presented to show the application of the proposed control strategy. © 2023 IEEE.

关键词： Model predictive control

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Integrating data-informativity conditions in predictor models for single module identification in dynamic networks

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IFAC-PapersOnLine 2023年第2期56卷 2377-2382页

作者： Paul M.J. Van den Hof Karthik R. Ramaswamy Stefanie J.M. Fonken Control Systems Group Department of Electrical Engineering Eindhoven University of Technology The Netherlands

For consistent identification of a target module in a dynamic network with the local direct method, basically two prime conditions need to be satisfied: (a) a set of structural conditions on the choice of the predictor model, i.e. a set of input and output node variables, and (b) conditions on data-informativity. While for conditions (a) constructive algorithms for node selection have been presented that appropriately guarantee that the identified object can indeed reveal the target module, the requirements for satisfying (b) have not yet been integrated fully. In this paper, we will present simplified path-based results for generic data-informativity, and show how they can be integrated in constructive algorithms for predictor model selection that provide consistent target module estimates. It is shown that data-informativity not only requires a sufficient number of external excitation signals to be present in the network, but also puts restrictions on the structure of the predictor model, i.e. the selection of input and output node variables. Some examples are presented to illustrate the new results.

关键词： System identification identifiability dynamic networks interconnected systems

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Efficient and Collaborative Decisions for Supplier-Customer Services Management

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Procedia Computer Science 2022年 214卷 1144-1151页

作者： Catalin Dimon Dumitru Popescu Radu Bîlbîie Department of Automatic Control and Systems Engineering UPB Bucharest Romania

The research work presents a original solution for increasing the efficiency on management Supplied-Customer Services (SCS), based on a causal graph configuration. This approach expresses the connection, interaction, and collaboration between the two main actors, suppliers and consumers of goods and products. The causal graph model is intended for management of supply resources, production capacities, transport activities and customer demands. Initial configuration of this a priori generated graph includes the suppliers and consumers distributed in nodes and the interconnections expressed by the arches of the graph. A causal operator is introduced, which offer the efficient decisions propagation for the estimated solution of the supplier-customer services (SCS) problem. The customers can be served by the corresponding suppliers, or the suppliers must satisfy the services of the consumers, respectively. The road traffic is chosen for transport activities at a specific model to traffic network and appropriate control to avoid congestion and increase the real-time traffic performances for (SCS) management. The effectiveness of the proposed approach is visible on large structures of the supply-customer networks in different industrial and economic fields.

关键词： supplier customer services causal graph control network transport system management

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Optimisation-Based Iterative Learning control for Distributed Consensus Tracking

Optimisation-Based Iterative Learning Control for Distribute...

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UKACC International Conference on control (control)

作者： Yueqing Zhang Bin Chen Bing Chu Zhan Shu Faculty of Engineering and Physical Sciences University of Southampton Southampton Department of Automatic Control and Systems Engineering University of Sheffield Sheffield U.K. Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

This paper addresses high-performance consensus tracking of repetitively operating networked dynamical systems using an iterative learning control (ILC) algorithm. It circumvents the need for precise model information in traditional methods and guarantees the high-performance by the predictive framework with a novel performance index that takes into account both current and future performance. The proposed algorithm ensures geometric convergence of the tracking error norm to zero and can be applied to both heterogeneous and non-minimum-phase systems. A distributed implementation of the algorithm is developed using the Alternating Direction Method of Multipliers, with detailed convergence analysis and numerical examples confirming its effectiveness.

关键词： System dynamics Heuristic algorithms Scholarships Predictive models Prediction algorithms Performance analysis Reliability

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A Novel Random Pulse Width Modulation for PMSM Drive System Based on Unified Voltage Modulation

A Novel Random Pulse Width Modulation for PMSM Drive System ...

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Energy, Power and Grid (ICEPG), International Conference on

作者： Jinpeng Kan Yongqing Meng Yixin Shi Fengjiao Li Wenjie Chen Changyi Li School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

The electromagnetic interference (EMI) problem caused by power electronic switching devices and pulse width modulation (PWM) affects the normal operation of the motor drive system. In this paper, a random PWM based on unified modulation is proposed for permanent magnet synchronous motor (PMSM) drive system. The theoretical basis of unified modulation and the implementation scheme of random modulation are analyzed. Finally, the effectiveness of the proposed random PWM is verified by simulation.

关键词： Motor drives Electromagnetic interference Voltage Switches Pulse width modulation Permanent magnet motors Power electronics Electromagnetics

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NPV analysis prediction of SRES with python tools

NPV analysis prediction of SRES with python tools

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2022 International Conference on Electronics and Renewable systems, ICEARS 2022

作者： Kulkarni, Haripriya H. Uttam, Satvik S. Londhe, Rohit A. Bapat, Sandeep C. PES'S Modern College of Engineering Department of Electrical Engineering Pune411005 India Feedback Control Systems Pune India

ISBN: (纸本)9781665484251

This paper highlights a Solar energy generation plant as Renewable energy source (SRES) on the criterion of cost involvement using net present value (NPV) method and its payback period. The Homer app is also used for analyzing a selected SRES system. The various big data analysis tools of python are discussed, which could be utilized effectively to analyze RES based on predicting the outcomes, like maximum generation capacity, optimum generation month, weather conditions and performance and many more. System integrity and SRES economic considerations are critically evaluated for an educational institution. The cost analysis using NPV method is included with the existing MAHADISCOM as one of the projects and SRES as another project. Both the projects are analyzed by assuming the lifespan of 11 years. The payback period of the SRES system is 3.3 years and hence after that, the energy will be available for free of cost through the mentioned system. This analysis is done for the site located in the state of Maharashtra, India, and can be used as a case study for engineering students for future perspectives. The tools used for data analysis of a RES project are found very useful for predictive analysis. In the present work Matplotlib and Seaborn tools of python are used for prediction of seasonal effect on generation of power. The new innovative method of big data analysis using python programming is applied to a case study and results are presented successfully. © 2022 IEEE.

关键词： Python

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Creating and Studying a Methodology for Calculating a Resistive Voltage Divider for Use in Electronic Voltage Transformers

Creating and Studying a Methodology for Calculating a Resist...

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International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： A.A. Yablokov A.V. Panashchatenko E.E. Gotovkina R.A. Maltsev Electric power systems automatic control department Electric systems department Ivanovo State Power Engineering University Ivanovo Russia

ISBN: (数字)9798331501105

ISBN: (纸本)9798331501112

In 2017 the Russian government approved a programme, Russian Federation Digital Economy, the main goal of which is to create an ecosystem with large scale use of digital format data in all fields of social and economic activity [1]. The electric power industry is being transformed in accordance with the concept, Digital Transformation 2030, developed by Russian Power Grids PLC [2]. Pursuant to this concept, electric substations under construction should be digital. At present, Russia has a number of operating digital substations (DSS) (Medvedevskaya SS, UVAT SS, Desna SS, Tobol SS [3]–[5], while many DSSs are at the design or construction stage. The creation of new substations, and also reconstruction of already operating ones, requires solving the problems of operating conventional electromagnetic current and voltage transformers. Electromagnetic voltage transformers (VT) are energy-inefficient, explosion – and flammability- hazardous equipment (due to their requiring additional charging with low consumption by micro-processing devices), with large weight and dimensions (an NKF-100 type transformer weighing 840 kg).

关键词： Resistors Resistance Substations Voltage measurement Voltage transformers Biological system modeling Spread spectrum communication Transformers Integrated circuit modeling Electromagnetics

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A Novel Zero Common-Mode Voltage Modulation Strategy for Dual Three-Phase PWM Inverter Based on Unified Voltage Modulation

A Novel Zero Common-Mode Voltage Modulation Strategy for Dua...

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Energy, Power and electrical engineering (EPEE), International Conference on

作者： Jinpeng Kan Yongqing Meng Changyi Li Wenjie Chen Fengjiao Li Yixin Shi School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

Power electronic switching devices and pulse width modulation (PWM) not only improves the performance of motor drive systems, but also brings about common-mode voltage (CMV) issues, that challenging the normal operation of the system. This article proposes a zero common-mode voltage modulation strategy based on unified voltage modulation for a 60° Y-connected six-phase permanent magnet synchronous motor system driven by a dual three-phase inverter. The theoretical basis and zero common-mode implementation scheme of unified modulation are analyzed, and the effectiveness of the proposed zero common-mode voltage modulation strategy is finally verified through simulation.

关键词： Pulse width modulation inverters Performance evaluation Simulation Modulation Voltage Switches Permanent magnet motors Inverters Permanent magnets Switching circuits

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Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach 25

Real-Time Object Detection and Robotic Manipulation for Agri...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Zhao, Hongyu Tang, Zezhi Li, Zhenhong Dong, Yi Si, Yuancheng Lu, Mingyang Panoutsos, George Imperial College The Department Of Physics London United Kingdom University Of Sheffield The Department Of Automatic Control And Systems Engineering SheffieldS1 3JD United Kingdom University Of Manchester The Department Of Electrical And Electronic Engineering Manchester United Kingdom University Of Southampton The Department Of Electronics And Computer Science Southampton United Kingdom Fudan University The Department Of Economics Shanghai200433 China AmesIA50011 United States

ISBN: (纸本)9798350340266

The optimization of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialization. Nowadays, the utilization of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of Convolutional Neural Networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The You Only Look Once(YOLO) algorithmic framework is employed with traditional Rectangular Bounding Boxes (R-Bbox) for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation. © 2024 IEEE.

关键词： Crops

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